Aligning climate scenarios to emissions inventories shifts global benchmarks.

Taking stock of global progress towards achieving the Paris Agreement requires consistently measuring aggregate national actions and pledges against modelled mitigation pathways1. However, national greenhouse gas inventories (NGHGIs) and scientific assessments of anthropogenic emissions follow different accounting conventions for land-based carbon fluxes resulting in a large difference in the present emission estimates2,3, a gap that will evolve over time. Using state-of-the-art methodologies4 and a land carbon-cycle emulator5, we align the Intergovernmental Panel on Climate Change (IPCC)-assessed mitigation pathways with the NGHGIs to make a comparison. We find that the key global mitigation benchmarks become harder to achieve when calculated using the NGHGI conventions, requiring both earlier net-zero CO2 timing and lower cumulative emissions. Furthermore, weakening natural carbon removal processes such as carbon fertilization can mask anthropogenic land-based removal efforts, with the result that land-based carbon fluxes in NGHGIs may ultimately become sources of emissions by 2100. Our results are important for the Global Stocktake6, suggesting that nations will need to increase the collective ambition of their climate targets to remain consistent with the global temperature goals.

Institutional decarbonization scenarios evaluated against the Paris Agreement 1.5 °C goal.

Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential institutional emission scenarios from the grey literature, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation.

Realization of Paris Agreement pledges may limit warming just below 2 °C.

Over the last five years prior to the Glasgow Climate Pact1, 154 Parties have submitted new or updated 2030 mitigation goals in their nationally determined contributions and 76 have put forward longer-term pledges. Quantifications of the pledges before the 2021 United Nations Climate Change Conference (COP26) suggested a less than 50 per cent chance of keeping warming below 2 degrees Celsius2-5. Here we show that warming can be kept just below 2 degrees Celsius if all conditional and unconditional pledges are implemented in full and on time. Peak warming could be limited to 1.9-2.0 degrees Celsius (5%-95% range 1.4-2.8 °C) in the full implementation case-building on a probabilistic characterization of Earth system uncertainties in line with the Working Group I contribution to the Sixth Assessment Report6 of the Intergovernmental Panel on Climate Change (IPCC). We retrospectively project twenty-first-century warming to show how the aggregate level of ambition changed from 2015 to 2021. Our results rely on the extrapolation of time-limited targets beyond 2030 or 2050, characteristics of the IPCC 1.5 °C Special Report (SR1.5) scenario database7 and the full implementation of pledges. More pessimistic assumptions on these factors would lead to higher temperature projections. A second, independent emissions modelling framework projected peak warming of 1.8 degrees Celsius, supporting the finding that realized pledges could limit warming to just below 2 degrees Celsius. Limiting warming not only to 'just below' but to 'well below' 2 degrees Celsius or 1.5 degrees Celsius urgently requires policies and actions to bring about steep emission reductions this decade, aligned with mid-century global net-zero CO2 emissions.

Can updated climate pledges limit warming well below 2°C?

Increased ambition and implementation are essential.

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios.

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.

A new scenario logic for the Paris Agreement long-term temperature goal.

To understand how global warming can be kept well below 2 degrees Celsius and even 1.5 degrees Celsius, climate policy uses scenarios that describe how society could reduce its greenhouse gas emissions. However, current scenarios have a key weakness: they typically focus on reaching specific climate goals in 2100. This choice may encourage risky pathways that delay action, reach higher-than-acceptable mid-century warming, and rely on net removal of carbon dioxide thereafter to undo their initial shortfall in reductions of emissions. Here we draw on insights from physical science to propose a scenario framework that focuses on capping global warming at a specific maximum level with either temperature stabilization or reversal thereafter. The ambition of climate action until carbon neutrality determines peak warming, and can be followed by a variety of long-term states with different sustainability implications. The approach proposed here closely mirrors the intentions of the United Nations Paris Agreement, and makes questions of intergenerational equity into explicit design choices.